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Create app.py
Browse files
app.py
ADDED
@@ -0,0 +1,607 @@
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1 |
+
import cv2
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2 |
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import streamlit as st
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3 |
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st.set_page_config(layout="wide")
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+
import streamlit.components.v1 as components
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import time
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import numpy as np
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import tensorflow as tf
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import matplotlib.pyplot as plt
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9 |
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import matplotlib.cm as cm
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10 |
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from PIL import Image
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11 |
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from tf_keras_vis.gradcam import Gradcam
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from io import BytesIO
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if "model" not in st.session_state:
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st.session_state.model = tf_model = tf.keras.models.load_model('best_model.h5')
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import base64
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import os
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19 |
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#****************************************/
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# GRAD CAM
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21 |
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#*********************************************#
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+
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gradcam = Gradcam(st.session_state.model, model_modifier=None, clone=False)
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+
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+
def generate_gradcam(pil_image, target_class):
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26 |
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# Convert PIL to array and preprocess
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img_array = np.array(pil_image)
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28 |
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img_preprocessed = tf.keras.applications.vgg16.preprocess_input(img_array.copy())
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29 |
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img_tensor = tf.expand_dims(img_preprocessed, axis=0)
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30 |
+
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31 |
+
# Generate heatmap
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32 |
+
loss = lambda output: tf.reduce_mean(output[:, target_class])
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cam = gradcam(loss, img_tensor, penultimate_layer=-1)
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34 |
+
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35 |
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# Process heatmap
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36 |
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cam = cam
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37 |
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if cam.ndim > 2:
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38 |
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cam = cam.squeeze()
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39 |
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cam = np.maximum(cam, 0)
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40 |
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cam = cv2.resize(cam, (224, 224))
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41 |
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cam = cam / cam.max() if cam.max() > 0 else cam
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42 |
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return cam
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43 |
+
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44 |
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def convert_image_to_base64(pil_image):
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45 |
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buffered = BytesIO()
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46 |
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pil_image.save(buffered, format="PNG")
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47 |
+
return base64.b64encode(buffered.getvalue()).decode()
|
48 |
+
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49 |
+
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50 |
+
#--------------------------------------------------#
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51 |
+
class_labels=[ 'Cyst', 'Normal','Stone', 'Tumor']
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52 |
+
def load_tensorflow_model():
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53 |
+
tf_model = tf.keras.models.load_model('best_model.h5')
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54 |
+
return tf_model
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55 |
+
def predict_image(image):
|
56 |
+
time.sleep(2)
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57 |
+
image = image.resize((224, 224))
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58 |
+
image = np.expand_dims(image, axis=0)
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59 |
+
predictions = st.session_state.model.predict(image)
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60 |
+
return predictions
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61 |
+
logo_path = "images/tensorflow.png"
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62 |
+
main_bg_ext = 'png'
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63 |
+
main_bg = 'images/bg1.jpg'
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64 |
+
# Read and encode the logo image
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65 |
+
with open(logo_path, "rb") as image_file:
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66 |
+
encoded_logo = base64.b64encode(image_file.read()).decode()
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67 |
+
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68 |
+
# Custom CSS to style the logo above the sidebar
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69 |
+
st.markdown(
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70 |
+
f"""
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71 |
+
<style>
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72 |
+
/* Container for logo and text */
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73 |
+
.logo-text-container {{
|
74 |
+
position: fixed;
|
75 |
+
top: 20px; /* Adjust vertical position */
|
76 |
+
left: 30px; /* Align with sidebar */
|
77 |
+
display: flex;
|
78 |
+
align-items: center;
|
79 |
+
gap: 5px;
|
80 |
+
width: 70%;
|
81 |
+
z-index:1000;
|
82 |
+
}}
|
83 |
+
|
84 |
+
/* Logo styling */
|
85 |
+
.logo-text-container img {{
|
86 |
+
width: 50px; /* Adjust logo size */
|
87 |
+
border-radius: 10px; /* Optional: round edges */
|
88 |
+
margin-top:-10px;
|
89 |
+
margin-left:-5px;
|
90 |
+
|
91 |
+
|
92 |
+
}}
|
93 |
+
|
94 |
+
/* Bold text styling */
|
95 |
+
.logo-text-container h1 {{
|
96 |
+
font-family: Nunito;
|
97 |
+
color: #0175C2;
|
98 |
+
font-size: 28px;
|
99 |
+
font-weight: bold;
|
100 |
+
margin-right :100px;
|
101 |
+
padding:0px;
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102 |
+
}}
|
103 |
+
.logo-text-container i{{
|
104 |
+
font-family: Nunito;
|
105 |
+
color: orange;
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106 |
+
font-size: 15px;
|
107 |
+
margin-right :10px;
|
108 |
+
padding:0px;
|
109 |
+
margin-left:-18.5%;
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110 |
+
margin-top:1%;
|
111 |
+
}}
|
112 |
+
/* Sidebar styling */
|
113 |
+
section[data-testid="stSidebar"][aria-expanded="true"] {{
|
114 |
+
margin-top: 100px !important; /* Space for the logo */
|
115 |
+
border-radius: 0 60px 0px 60px !important; /* Top-left and bottom-right corners */
|
116 |
+
width: 200px !important; /* Sidebar width */
|
117 |
+
background:none; /* Gradient background */
|
118 |
+
/* box-shadow: 0px 4px 8px rgba(0, 0, 0, 0.2); /* Shadow effect */
|
119 |
+
/* border: 1px solid #FFD700; /* Shiny golden border */
|
120 |
+
margin-bottom: 1px !important;
|
121 |
+
color:white !important;
|
122 |
+
|
123 |
+
}}
|
124 |
+
header[data-testid="stHeader"] {{
|
125 |
+
/*background: transparent !important;*/
|
126 |
+
background: white;
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127 |
+
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128 |
+
/*margin-right: 10px !important;*/
|
129 |
+
margin-top: 0.5px !important;
|
130 |
+
z-index: 1 !important;
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131 |
+
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132 |
+
color: orange; /* White text */
|
133 |
+
font-family: "Times New Roman " !important; /* Font */
|
134 |
+
font-size: 18px !important; /* Font size */
|
135 |
+
font-weight: bold !important; /* Bold text */
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136 |
+
padding: 10px 20px; /* Padding for buttons */
|
137 |
+
border: none; /* Remove border */
|
138 |
+
border-radius: 1px; /* Rounded corners */
|
139 |
+
box-shadow: 0px 4px 10px rgba(0, 0, 0, 0.2); /* Shadow effect */
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140 |
+
transition: all 0.3s ease-in-out; /* Smooth transition */
|
141 |
+
align-items: left;
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142 |
+
justify-content: center;
|
143 |
+
/*margin: 10px 0;*/
|
144 |
+
width:100%;
|
145 |
+
height:80px;
|
146 |
+
backdrop-filter: blur(10px);
|
147 |
+
border: 2px solid rgba(255, 255, 255, 0.4); /* Light border */
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148 |
+
|
149 |
+
|
150 |
+
}}
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151 |
+
div[data-testid="stDecoration"]{{
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152 |
+
background-image:none;
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153 |
+
}}
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154 |
+
div[data-testid="stApp"]{{
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155 |
+
/*background: grey;*/
|
156 |
+
background: rgba(255, 255, 255, 0.5); /* Semi-transparent white background */
|
157 |
+
|
158 |
+
height: 100vh; /* Full viewport height */
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159 |
+
width: 99.5%;
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160 |
+
border-radius: 2px !important;
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161 |
+
margin-left:5px;
|
162 |
+
margin-right:5px;
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163 |
+
margin-top:0px;
|
164 |
+
/* box-shadow: 0px 4px 10px rgba(0, 0, 0, 0.2); /* Shadow effect */
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165 |
+
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166 |
+
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167 |
+
background: url(data:image/{main_bg_ext};base64,{base64.b64encode(open(main_bg, "rb").read()).decode()});
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168 |
+
background-size: cover; /* Ensure the image covers the full page */
|
169 |
+
background-position: center;
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170 |
+
|
171 |
+
overflow: hidden;
|
172 |
+
|
173 |
+
}}
|
174 |
+
.content-container {{
|
175 |
+
background-color: rgba(173, 216, 230, 0.5); /* Light blue with 50% transparency */
|
176 |
+
backdrop-filter: blur(10px); /* Adds a slight blur effect */ border-radius: 1px;
|
177 |
+
width: 28%;
|
178 |
+
margin-left: 150px;
|
179 |
+
/* margin-top: -60px;*/
|
180 |
+
margin-bottom: 10px;
|
181 |
+
margin-right:10px;
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182 |
+
padding:0;
|
183 |
+
/* border-radius:0px 0px 15px 15px ;*/
|
184 |
+
border:1px solid transparent;
|
185 |
+
overflow-y: auto; /* Enable vertical scrolling for the content */
|
186 |
+
position: fixed; /* Fix the position of the container */
|
187 |
+
top: 10%; /* Adjust top offset */
|
188 |
+
left: 60%; /* Adjust left offset */
|
189 |
+
height: 89.5vh; /* Full viewport height */
|
190 |
+
|
191 |
+
}}
|
192 |
+
.content-container2 {{
|
193 |
+
background-color: rgba(0, 0, 0, 0.1); /* Light blue with 50% transparency */
|
194 |
+
backdrop-filter: blur(10px); /* Adds a slight blur effect */ border-radius: 1px;
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195 |
+
width: 90%;
|
196 |
+
margin-left: 10px;
|
197 |
+
/* margin-top: -10px;*/
|
198 |
+
margin-bottom: 160px;
|
199 |
+
margin-right:10px;
|
200 |
+
padding:0;
|
201 |
+
border-radius:1px ;
|
202 |
+
border:1px solid transparent;
|
203 |
+
overflow-y: auto; /* Enable vertical scrolling for the content */
|
204 |
+
position: fixed; /* Fix the position of the container */
|
205 |
+
top: 3%; /* Adjust top offset */
|
206 |
+
left: 2.5%; /* Adjust left offset */
|
207 |
+
height: 78vh; /* Full viewport height */
|
208 |
+
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209 |
+
}}
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210 |
+
.content-container4 {{
|
211 |
+
background-color: rgba(0, 0, 0, 0.1); /* Light blue with 50% transparency */
|
212 |
+
backdrop-filter: blur(10px); /* Adds a slight blur effect */ width: 40%;
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213 |
+
margin-left: 10px;
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214 |
+
margin-bottom: 160px;
|
215 |
+
margin-right:10px;
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216 |
+
padding:0;
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217 |
+
overflow-y: auto; /* Enable vertical scrolling for the content */
|
218 |
+
position: fixed; /* Fix the position of the container */
|
219 |
+
top: 60%; /* Adjust top offset */
|
220 |
+
left: 2.5%; /* Adjust left offset */
|
221 |
+
height: 10vh; /* Full viewport height */
|
222 |
+
|
223 |
+
}}
|
224 |
+
.content-container4 h3 ,p {{
|
225 |
+
font-family: "Times New Roman" !important; /* Elegant font for title */
|
226 |
+
font-size: 1rem;
|
227 |
+
font-weight: bold;
|
228 |
+
text-align:center;
|
229 |
+
}}
|
230 |
+
.content-container5 h3 ,p {{
|
231 |
+
font-family: "Times New Roman" !important; /* Elegant font for title */
|
232 |
+
font-size: 1rem;
|
233 |
+
font-weight: bold;
|
234 |
+
text-align:center;
|
235 |
+
}}
|
236 |
+
.content-container6 h3 ,p {{
|
237 |
+
font-family: "Times New Roman" !important; /* Elegant font for title */
|
238 |
+
font-size: 1rem;
|
239 |
+
font-weight: bold;
|
240 |
+
text-align:center;
|
241 |
+
}}
|
242 |
+
.content-container7 h3 ,p {{
|
243 |
+
font-family: "Times New Roman" !important; /* Elegant font for title */
|
244 |
+
font-size: 1rem;
|
245 |
+
font-weight: bold;
|
246 |
+
text-align:center;
|
247 |
+
}}
|
248 |
+
.content-container5 {{
|
249 |
+
background-color: rgba(0, 0, 0, 0.1); /* Light blue with 50% transparency */
|
250 |
+
backdrop-filter: blur(10px); /* Adds a slight blur effect */ width: 40%;
|
251 |
+
margin-left: 180px;
|
252 |
+
margin-bottom: 130px;
|
253 |
+
margin-right:10px;
|
254 |
+
padding:0;
|
255 |
+
overflow-y: auto; /* Enable vertical scrolling for the content */
|
256 |
+
position: fixed; /* Fix the position of the container */
|
257 |
+
top: 60%; /* Adjust top offset */
|
258 |
+
left: 5.5%; /* Adjust left offset */
|
259 |
+
height: 10vh; /* Full viewport height */
|
260 |
+
|
261 |
+
}}
|
262 |
+
.content-container3 {{
|
263 |
+
background-color: rgba(216, 216, 230, 0.5); /* Light blue with 50% transparency */
|
264 |
+
backdrop-filter: blur(10px); /* Adds a slight blur effect */ border-radius: 1px;
|
265 |
+
width: 92%;
|
266 |
+
margin-left: 10px;
|
267 |
+
/* margin-top: -10px;*/
|
268 |
+
margin-bottom: 160px;
|
269 |
+
margin-right:10px;
|
270 |
+
padding:0;
|
271 |
+
border: 10px solid white;
|
272 |
+
overflow-y: auto; /* Enable vertical scrolling for the content */
|
273 |
+
position: fixed; /* Fix the position of the container */
|
274 |
+
top: 3%; /* Adjust top offset */
|
275 |
+
left: 1.5%; /* Adjust left offset */
|
276 |
+
height: 40vh; /* Full viewport height */
|
277 |
+
|
278 |
+
}}
|
279 |
+
.content-container6 {{
|
280 |
+
background-color: rgba(0, 0, 0, 0.1); /* Light blue with 50% transparency */
|
281 |
+
backdrop-filter: blur(10px); /* Adds a slight blur effect */ width: 40%;
|
282 |
+
margin-left: 10px;
|
283 |
+
margin-bottom: 160px;
|
284 |
+
margin-right:10px;
|
285 |
+
padding:0;
|
286 |
+
overflow-y: auto; /* Enable vertical scrolling for the content */
|
287 |
+
position: fixed; /* Fix the position of the container */
|
288 |
+
top: 80%; /* Adjust top offset */
|
289 |
+
left: 2.5%; /* Adjust left offset */
|
290 |
+
height: 10vh; /* Full viewport height */
|
291 |
+
|
292 |
+
}}
|
293 |
+
.content-container7 {{
|
294 |
+
background-color: rgba(0, 0, 0, 0.1); /* Light blue with 50% transparency */
|
295 |
+
backdrop-filter: blur(10px); /* Adds a slight blur effect */ width: 40%;
|
296 |
+
margin-left: 180px;
|
297 |
+
margin-bottom: 130px;
|
298 |
+
margin-right:10px;
|
299 |
+
padding:0;
|
300 |
+
overflow-y: auto; /* Enable vertical scrolling for the content */
|
301 |
+
position: fixed; /* Fix the position of the container */
|
302 |
+
top: 80%; /* Adjust top offset */
|
303 |
+
left: 5.5%; /* Adjust left offset */
|
304 |
+
height: 10vh; /* Full viewport height */
|
305 |
+
|
306 |
+
}}
|
307 |
+
.content-container2 img {{
|
308 |
+
width:99%;
|
309 |
+
height:50%;
|
310 |
+
|
311 |
+
}}
|
312 |
+
.content-container3 img {{
|
313 |
+
width:100%;
|
314 |
+
height:100%;
|
315 |
+
|
316 |
+
}}
|
317 |
+
div.stButton > button {{
|
318 |
+
background: rgba(255, 255, 255, 0.2);
|
319 |
+
color: blue; /* White text */
|
320 |
+
font-family: "Times New Roman " !important; /* Font */
|
321 |
+
font-size: 18px !important; /* Font size */
|
322 |
+
font-weight: bold !important; /* Bold text */
|
323 |
+
padding: 10px 20px; /* Padding for buttons */
|
324 |
+
border: none; /* Remove border */
|
325 |
+
border-radius: 15px; /* Rounded corners */
|
326 |
+
box-shadow: 0px 4px 10px rgba(0, 0, 0, 0.2); /* Shadow effect */
|
327 |
+
transition: all 0.3s ease-in-out; /* Smooth transition */
|
328 |
+
display: flex;
|
329 |
+
align-items: center;
|
330 |
+
justify-content: center;
|
331 |
+
margin: 10px 0;
|
332 |
+
width:170px;
|
333 |
+
height:60px;
|
334 |
+
backdrop-filter: blur(10px);
|
335 |
+
|
336 |
+
}}
|
337 |
+
|
338 |
+
/* Hover effect */
|
339 |
+
div.stButton > button:hover {{
|
340 |
+
background: rgba(255, 255, 255, 0.2);
|
341 |
+
box-shadow: 0px 6px 12px rgba(0, 0, 0, 0.4); /* Enhanced shadow on hover */
|
342 |
+
transform: scale(1.05); /* Slightly enlarge button */
|
343 |
+
transform: scale(1.1); /* Slight zoom on hover */
|
344 |
+
box-shadow: 0px 4px 12px rgba(255, 255, 255, 0.4); /* Glow effect */
|
345 |
+
}}
|
346 |
+
.titles{{
|
347 |
+
margin-top:50px !important;
|
348 |
+
}}
|
349 |
+
/* Title styling */
|
350 |
+
.titles h1{{
|
351 |
+
/*font-family: "Times New Roman" !important; /* Elegant font for title */
|
352 |
+
/* font-size: 2.9rem;*/
|
353 |
+
/*font-weight: bold;*/
|
354 |
+
margin-left: 5px;
|
355 |
+
/* margin-top:-50px;*/
|
356 |
+
margin-bottom:50px;
|
357 |
+
padding: 0;
|
358 |
+
color: black; /* Neutral color for text */
|
359 |
+
}}
|
360 |
+
.titles > div{{
|
361 |
+
font-family: "Times New Roman" !important; /* Elegant font for title */
|
362 |
+
font-size: 1.2rem;
|
363 |
+
margin-left: 5px;
|
364 |
+
margin-bottom:1px;
|
365 |
+
padding: 0;
|
366 |
+
color:black; /* Neutral color for text */
|
367 |
+
}}
|
368 |
+
/* Recently viewed section */
|
369 |
+
.recently-viewed {{
|
370 |
+
display: flex;
|
371 |
+
align-items: center;
|
372 |
+
justify-content: flex-start; /* Align items to the extreme left */
|
373 |
+
margin-bottom: 10px;
|
374 |
+
margin-top: 20px;
|
375 |
+
gap: 10px; /* Add spacing between the elements */
|
376 |
+
padding-left: 20px; /* Add some padding if needed */
|
377 |
+
margin-left:35px;
|
378 |
+
height:100px;
|
379 |
+
|
380 |
+
}}
|
381 |
+
|
382 |
+
|
383 |
+
|
384 |
+
|
385 |
+
|
386 |
+
/* Style for the upload button */
|
387 |
+
[class*="st-key-upload-btn"] {{
|
388 |
+
position: absolute;
|
389 |
+
top: 100%; /* Position from the top of the inner circle */
|
390 |
+
left: -3%; /* Position horizontally at the center */
|
391 |
+
padding: 10px 20px;
|
392 |
+
color: red;
|
393 |
+
border: none;
|
394 |
+
border-radius: 20px;
|
395 |
+
cursor: pointer;
|
396 |
+
font-size: 35px !important;
|
397 |
+
width:30px;
|
398 |
+
height:20px;
|
399 |
+
}}
|
400 |
+
|
401 |
+
.upload-btn:hover {{
|
402 |
+
background-color: rgba(0, 123, 255, 1);
|
403 |
+
}}
|
404 |
+
div[data-testid="stFileUploader"] label > div > p {{
|
405 |
+
display:none;
|
406 |
+
color:white !important;
|
407 |
+
}}
|
408 |
+
section[data-testid="stFileUploaderDropzone"] {{
|
409 |
+
width:200px;
|
410 |
+
height: 60px;
|
411 |
+
background-color: white;
|
412 |
+
border-radius: 40px;
|
413 |
+
display: flex;
|
414 |
+
justify-content: center;
|
415 |
+
align-items: center;
|
416 |
+
margin-top:-10px;
|
417 |
+
box-shadow: 0px 4px 8px rgba(0, 0, 0, 0.3);
|
418 |
+
margin:20px;
|
419 |
+
background-color: rgba(255, 255, 255, 0.7); /* Transparent blue background */
|
420 |
+
color:white;
|
421 |
+
}}
|
422 |
+
div[data-testid="stFileUploaderDropzoneInstructions"] div > small{{
|
423 |
+
color:white !important;
|
424 |
+
display:none;
|
425 |
+
}}
|
426 |
+
div[data-testid="stFileUploaderDropzoneInstructions"] span{{
|
427 |
+
margin-left:65px;
|
428 |
+
color:orange;
|
429 |
+
}}
|
430 |
+
div[data-testid="stFileUploaderDropzoneInstructions"] div{{
|
431 |
+
display:none;
|
432 |
+
}}
|
433 |
+
section[data-testid="stFileUploaderDropzone"] button{{
|
434 |
+
display:none;
|
435 |
+
}}
|
436 |
+
div[data-testid="stMarkdownContainer"] p {{
|
437 |
+
font-family: "Times New Roman" !important; /* Elegant font for title */
|
438 |
+
color:white !important;
|
439 |
+
}}
|
440 |
+
.highlight {{
|
441 |
+
border: 4px solid lime;
|
442 |
+
font-weight: bold;
|
443 |
+
background: radial-gradient(circle, rgba(0,255,0,0.3) 0%, rgba(0,0,0,0) 70%);
|
444 |
+
box-shadow: 0px 0px 30px 10px rgba(0, 255, 0, 0.9),
|
445 |
+
0px 0px 60px 20px rgba(0, 255, 0, 0.6),
|
446 |
+
inset 0px 0px 15px rgba(0, 255, 0, 0.8);
|
447 |
+
transition: all 0.3s ease-in-out;
|
448 |
+
|
449 |
+
}}
|
450 |
+
.highlight:hover {{
|
451 |
+
transform: scale(1.05);
|
452 |
+
background: radial-gradient(circle, rgba(0,255,0,0.6) 0%, rgba(0,0,0,0) 80%);
|
453 |
+
box-shadow: 0px 0px 40px 15px rgba(0, 255, 0, 1),
|
454 |
+
0px 0px 70px 30px rgba(0, 255, 0, 0.7),
|
455 |
+
inset 0px 0px 20px rgba(0, 255, 0, 1);
|
456 |
+
}}
|
457 |
+
</style>
|
458 |
+
<div class="logo-text-container">
|
459 |
+
<img src="data:image/png;base64,{encoded_logo}" alt="Logo">
|
460 |
+
<h1>KidneyScan AI<br>
|
461 |
+
|
462 |
+
</h1>
|
463 |
+
<i>Empowering Early Diagnosis with AI</ai>
|
464 |
+
|
465 |
+
|
466 |
+
</div>
|
467 |
+
""", unsafe_allow_html=True
|
468 |
+
)
|
469 |
+
loading_html = """
|
470 |
+
<style>
|
471 |
+
.loader {
|
472 |
+
border: 8px solid #f3f3f3;
|
473 |
+
border-top: 8px solid #0175C2; /* Blue color */
|
474 |
+
border-radius: 50%;
|
475 |
+
width: 50px;
|
476 |
+
height: 50px;
|
477 |
+
animation: spin 1s linear infinite;
|
478 |
+
margin: auto;
|
479 |
+
}
|
480 |
+
@keyframes spin {
|
481 |
+
0% { transform: rotate(0deg); }
|
482 |
+
100% { transform: rotate(360deg); }
|
483 |
+
}
|
484 |
+
|
485 |
+
</style>
|
486 |
+
<div class="loader"></div>
|
487 |
+
"""
|
488 |
+
|
489 |
+
page = "Home"
|
490 |
+
|
491 |
+
# Display content based on the selected page
|
492 |
+
# Define the page content dynamically
|
493 |
+
if page == "Home":
|
494 |
+
|
495 |
+
|
496 |
+
#components.html(html_string) # JavaScript works
|
497 |
+
#st.markdown(html_string, unsafe_allow_html=True)
|
498 |
+
image_path = "images/download.jfif"
|
499 |
+
|
500 |
+
st.container()
|
501 |
+
st.markdown(f"""
|
502 |
+
|
503 |
+
<div class="titles">
|
504 |
+
<h1>Kidney Disease Classfication</br> Using Transfer learning</h1>
|
505 |
+
<div> This web application utilizes deep learning to classify kidney ultrasound images</br>
|
506 |
+
into four categories: Normal, Cyst, Tumor, and Stone Class.
|
507 |
+
Built with Streamlit and powered by </br>a TensorFlow transfer learning
|
508 |
+
model based on <strong>VGG16</strong>
|
509 |
+
the app provides a simple and efficient way for users </br>
|
510 |
+
to upload kidney scans and receive instant predictions. The model analyzes the image
|
511 |
+
and classifies it based </br>on learned patterns, offering a confidence score for better interpretation.
|
512 |
+
</div>
|
513 |
+
</div>
|
514 |
+
""",
|
515 |
+
unsafe_allow_html=True,
|
516 |
+
)
|
517 |
+
uploaded_file = st.file_uploader("Choose a file", type=["png", "jpg", "jpeg"],key="upload-btn")
|
518 |
+
if uploaded_file is not None:
|
519 |
+
images = Image.open(uploaded_file)
|
520 |
+
# Rewind file pointer to the beginning
|
521 |
+
uploaded_file.seek(0)
|
522 |
+
|
523 |
+
file_content = uploaded_file.read() # Read file once
|
524 |
+
# Convert to base64 for HTML display
|
525 |
+
encoded_image = base64.b64encode(file_content).decode()
|
526 |
+
# Read and process image
|
527 |
+
pil_image = Image.open(uploaded_file).convert('RGB').resize((224, 224))
|
528 |
+
img_array = np.array(pil_image)
|
529 |
+
|
530 |
+
prediction = predict_image(images)
|
531 |
+
max_index = int(np.argmax(prediction[0]))
|
532 |
+
print(f"max index:{max_index}")
|
533 |
+
max_score = prediction[0][max_index]
|
534 |
+
predicted_class = np.argmax(prediction[0])
|
535 |
+
|
536 |
+
highlight_class = "highlight" # Special class for the highest confidence score
|
537 |
+
|
538 |
+
|
539 |
+
# Generate Grad-CAM
|
540 |
+
cam = generate_gradcam(pil_image, predicted_class)
|
541 |
+
|
542 |
+
# Create overlay
|
543 |
+
heatmap = cm.jet(cam)[..., :3]
|
544 |
+
heatmap = (heatmap * 255).astype(np.uint8)
|
545 |
+
overlayed_image = cv2.addWeighted(img_array, 0.6, heatmap, 0.4, 0)
|
546 |
+
|
547 |
+
# Convert to PIL
|
548 |
+
overlayed_pil = Image.fromarray(overlayed_image)
|
549 |
+
# Convert to base64
|
550 |
+
orig_b64 = convert_image_to_base64(pil_image)
|
551 |
+
overlay_b64 = convert_image_to_base64(overlayed_pil)
|
552 |
+
content = f"""
|
553 |
+
<div class="content-container">
|
554 |
+
<!-- Title -->
|
555 |
+
<!-- Recently Viewed Section -->
|
556 |
+
<div class="content-container2">
|
557 |
+
<div class="content-container3">
|
558 |
+
<img src="data:image/png;base64,{orig_b64}" alt="Uploaded Image">
|
559 |
+
</div>
|
560 |
+
<div class="content-container3">
|
561 |
+
<img src="data:image/png;base64,{overlay_b64}" class="result-image">
|
562 |
+
</div>
|
563 |
+
<div class="content-container4 {'highlight' if max_index == 0 else ''}">
|
564 |
+
<h3>{class_labels[0]}</h3>
|
565 |
+
<p>T Score: {prediction[0][0]:.2f}</p>
|
566 |
+
</div>
|
567 |
+
<div class="content-container5 {'highlight' if max_index == 1 else ''}">
|
568 |
+
<h3> {class_labels[1]}</h3>
|
569 |
+
<p>T Score: {prediction[0][1]:.2f}</p>
|
570 |
+
</div>
|
571 |
+
<div class="content-container6 {'highlight' if max_index == 2 else ''}">
|
572 |
+
<h3> {class_labels[2]}</h3>
|
573 |
+
<p>T Score: {prediction[0][2]:.2f}</p>
|
574 |
+
</div>
|
575 |
+
<div class="content-container7 {'highlight' if max_index == 3 else ''}">
|
576 |
+
<h3>{class_labels[3]}</h3>
|
577 |
+
<p>T Score: {prediction[0][3]:.2f}</p>
|
578 |
+
</div>
|
579 |
+
|
580 |
+
|
581 |
+
"""
|
582 |
+
|
583 |
+
# Close the gallery and content div
|
584 |
+
|
585 |
+
# Render the content
|
586 |
+
st.markdown(content, unsafe_allow_html=True)
|
587 |
+
else:
|
588 |
+
default_image_path = "images/download.jfif"
|
589 |
+
with open(image_path, "rb") as image_file:
|
590 |
+
encoded_image = base64.b64encode(image_file.read()).decode()
|
591 |
+
|
592 |
+
|
593 |
+
st.markdown(f"""
|
594 |
+
<div class="content-container">
|
595 |
+
<!-- Title -->
|
596 |
+
<!-- Recently Viewed Section -->
|
597 |
+
<div class="content-container2">
|
598 |
+
<div class="content-container3">
|
599 |
+
<img src="data:image/png;base64,{encoded_image}" alt="Default Image">
|
600 |
+
</div>
|
601 |
+
</div>
|
602 |
+
|
603 |
+
""",
|
604 |
+
unsafe_allow_html=True,
|
605 |
+
)
|
606 |
+
|
607 |
+
|